Process operators, production planners, and maintenance personnel in industrial process environments must routinely make decisions about the utilization of their production assets. They want to know the productive capability of assets needed for successful completion of scheduled output. Operators and production managers routinely adjust the operational parameters of the available assets to tune their processes for greater efficiency, to maximize production output, or to safeguard a weakened asset in an attempt to finish a batch or production run before a machine breaks down.
Traditionally such persons rely on the loose integration of independent systems, input from their maintenance departments, or the advice of expert machine analysts. To keep abreast of machine conditions various approaches are utilized, such as periodic walk-around vibration programs or online continuous monitoring systems. Most of these systems focus on collecting data that is typically transported to a central location for offline analysis by an expert.
These systems are seldom well understood by the operators and production planners. They are in the domain of the maintenance or machine reliability departments and require significant training and expertise. Timely feedback which could be used to adjust the production process is rarely available. A few of the online offerings attempt to provide some local annunciation mechanism based on limits applied to measured values, but these typically comprise merely a relay closure to light a lamp or sound an alert. This type of indication is of little use to an operator in the control room.
Many systems rely on simple thresholds, ratios to baselines and statistics to trigger alarms or indicate machine condition. Some systems rely on remote host processors or other secondary systems running software expert systems to diagnose specific machine faults, but these techniques are typically hampered by the limited availability of data and their remote location.
Some prior systems, such as the Distributed Diagnostic System described in U.S. Pat. No. 6,199,018, have attempted to simplify reporting of condition information with green, yellow, and red indicators. Unfortunately, this does not give the operators or planners a real sense of the productive capability or stability of a machine. For example, if a machine was operating in the green condition and goes yellow, was it running in the green just below the yellow threshold and now has changed only slightly to run yellow, or has it moved from far down in the green to very high in the yellow (i.e., almost red)? If one must choose between whether to keep an asset active in production or alter the process, a machine analyst (if available) would be required to help make the decision.
In general, the output of all these systems is discrete, which is a simple indication that further investigation is required. The only analog data provided, if any, are the actual measured raw values. All of these approaches still require a machine fault expert who is familiar with the criticality of specific parameters or even the seriousness of specific faults to make judgment calls.
What is needed, therefore, is a machine condition indication system that produces advisory health information in a format that an untrained and relatively inexperienced person can successfully use to make operational or productive capacity judgments relative to their available production assets. Also needed is a system that provides advisory health information in such a manner that it is amenable for use by automated agents responsible for tuning a particular control system. Such capabilities would encourage awareness of the impact a process has on the production assets and enable production installations to manage these assets in an informed manner, rather than running strictly by-the-book or simply guessing.